Unraveling Alzheimer's: The Effects of Tau on AB Protein Aggregation

Alzheimer’s is a neurodegenerative disease characterized by the formation of extracellular amyloid-beta (abeta or AB) plaques and intracellular tau plaques. This experiment explores whether the presence of normal tau-441 protein augments AB-42 aggregation. The concentration at which each protein self-aggregated was identified by creating aggregation curves. A control and experimental aliquot of AB/buffer and AB/tau respectively were then scanned at regular intervals to determine the rate amount of aggregation in each. The conclusion is that tau moderately augments AB aggregation, possibly by stabilizing the developing plaque.

Introduction

Alzheimer’s Disease is a neurodegenerative disease that progressively destroys regions of the brain, including those responsible for motor and memory skills. It is the leading cause of dementia among adults above sixty years old and the sixth leading cause of death in the United States. Scientists are investigating Alzheimer’s underlying molecular mechanisms to produce effective treatments. Of particular interest are the pathways of tau and AB protein, each of which contributes to the brain’s overall degeneration.

This experiment simulates direct tau-AB interaction prior to apoptosis, or programmed cell death. In vivo, such an interaction that could result after cytotoxic (“toxic to living cells”) AB oligomers puncture through the cell membrane and allow cytoplasmic exchange across the extracellular matrix. The aggregation rate of tau-induced AB is compared to that of AB in a control aliquot.

Background Information

Alzheimer's Disease is characterized by the formation of intracellular tau protein neurofibrillary tangles (NFTs) and extracellular amyloid-beta (AB) plaques. Both are “clumps” of misfolded protein. The formation pathway of each is described as follows.

AB monomers are formed outside of the cell from the cleavage of Amyloid precursor protein (APP). AB monomers may join together as oligomers. An oligomer is a polymer that has comparatively few repeating units. It can punch holes in the cell membranes of neurons5 and lead to synaptic failure. AB oligomers are the precursor to AB fibrils, which form aggregated AB plaques. Traditional research in Alzheimer’s has been largely based on the premise that AB plaques are responsible for dementia in clinical patients. Some studies, however, show that there is a poor correlation between the two. Some speculate that AB plaques may even protect the brain by limiting the existence of cytotoxic AB oligomers, which can punch holes in the cell membrane.5 Put another way, aggregated AB is more toxic in oligomeric form than in fibrillar form.

Tau is a microtubule-stabilizing protein. Tau NFTs are thought to form as a result of hyperphosphorylation, one of the signaling mechanisms used by the cell to regulate mitosis. The aggregation of tau fibrils within neuronal bodies eventually bursts the cell membrane. An extracellular “ghost tangle” remains, attached to a plaque with tau protein fragments. The tau hypothesis states that tau, rather than AB, is responsible for the onset of Alzheimer’s as NFTs consume normal tau and spread to other neurons. Tau tangles may appear twenty years in advance of clinical symptoms.

In summary, tau NFTs are intracellular and created by hyperphosphorylation. AB plaques are extracellular and created by aggregation. The puncturing of the cell membrane due to AB oligomers provides a means for NFTs and plaques to interact directly. Past in vitro experiments have shown that direct interaction between AB and tau induces tau aggregation and hyperphosphorylation and AB disassembly.

Objective and Hypothesis

This experiment investigates how the presence of tau affects AB aggregation by comparing aggregation rates in an experimental tau-AB aliquot, a control AB aliquot, and positive and negative controls. It is hypothesized that the addition of tau will increase AB aggregation as measured through fluorescence microscopy.

A trial run was first performed on the plate reader to ensure it was functioning properly using 50 µL aliquots of stock fluorescent dye. The microplate reader observed negligible signals as expected due to the lack of an analyte.

The Proteostat Detection Reagent functions by binding to a protein or other sample. A microplate reader can then excite the analyte at a specific wavelength causing it to fluoresce. The light emitted from the analyte is collected and measured by the microplate reader to identify the amount of aggregation present. A stock of 200 µM loading solution was created with Detection Reagent and 1X buffer to be aliquoted as needed.

The positive and negative controls provided in the Proteostat aggregation assay kit were scanned at stepwise concentrations to create a base aggregation curve, in which fluorescence increases with protein aggregation. Ten 40 µM aliquots of each control were created and serially diluted to achieve a range of aliquots from 40 µM to 0.078 µM. While the negative control expressed negligible aggregation, the positive control curve was used as a quantitative reference for tau and AB solutions.

Aggregation curves were created for tau and AB to determine the critical concentration at which self-aggregation occurred. Both proteins were serially diluted using 200 µM stock solutions and scanned by the microplate reader. Tau did not self-aggregate in response to increasing concentrations, while AB’s critical concentration was found to be 0.05 mg/mL.

In the final phase of the experiment, tau was added to an aliquot of AB at its critical concentration and scanned for aggregation. Four controls were simultaneously scanned: an AB-buffer aliquot, the provided positive and negative Detection Reagent controls, and a 1X buffer aliquot. All five aliquots aliquot were created in a two-step process. The first set of analytes were added to a 96-well plate. 1 µL of pure Detection Reagent was added to each well. The well plate was incubated for 15 minutes before being scanned for aggregation by the microplate reader. The second set of analytes was then added. Another 1 µL of Detection Reagent was added to each well. The entire plate was incubated for 10 minutes before being scanned at 10-minute intervals.

Data

Figure 1

Preliminary AB Aggregation Data Table

Approximate Concentration (mg/mL)

Relative Fluorescence Units (RFUs)

0.2

2084

0.1

1091

0.05 (Self-aggregation)

596

0.025

172

0.013

127

0.006

53

0.003

22

0.002

17

Figure 2

Aggregation Curves (Tau, Abeta, Pos. and Neg. Controls)

Y-Axis: Relative Fluorescence Units (RFUs)

X-Axis: Well Number

Note: Concentration starts at 2 µM in Well 1 and decreases by a factor of 2 for each well

*Dissociation of each well’s contents occurs between the first (0 min) and second (18 min) data points in Figure 5, after the addition of the second analyte disturbs each well. As such the second data point in Figure 5 is the first data point in Figure 6.

Discussion

This experiment was only performed once due to limited materials, making the stated analysis explicitly preliminary. Additional trials must be conducted to determine if the results are statistically significant and replicable.

Figure 1 denotes the change in aggregation as concentration decreases for AB. Between 0.05 and 0.025 mg/mL the RFU reading falls from 596 to 172, a ratio of 3.46—the largest contrast compared to other consecutive RFU readings. For the purposes of this experiment, 0.05 mg/mL was adopted as the concentration at which AB self-aggregates.

Figure 2 compares the aggregation curves of AB, tau, and the provided positive and negative controls. The AB curve is shown to closely follow the positive control curve. The tau curve closely follows the negative control curve, suggesting that it does not self-aggregate at the tested concentration range.

On average the experimental tau-AB aliquot had 2.66 times as much aggregation compared to the positive and negative control aliquots. The experimental aliquot increased in overall aggregation by 18.7%, the AB control aliquot by -12.2%, and the Positive control by 6.4% (Figures 3, 4). The line of best fit in Figure 5 shows that the experimental aliquot aggregated at an average rate of 1.2065 RFUs/min, while the AB control aliquot aggregated at an average rate of 0.2179 RFUs/min. The rate of the former is approximately 5.5 times faster than the latter. The buffer aliquot expressed zero aggregation throughout the entire reading.

Interestingly, both the experimental and AB control aliquots remained well below the 596-RFU benchmark for AB self-aggregation. Possible explanations are that the AB dissociated during incubation or that the benchmark was not reflective of the true critical concentration. Interestingly, the positive control aliquot in Figure 4 exhibited extreme variation, jumping from 1432.5 to 3452 to 1385 RFUs in the first three points. The most plausible explanation is that excess, unaggregated lyzozyme was present.

The first data point in Figure 5 should be the same, but are 350 and 285.5 RFUs for the experimental and AB control aliquots respectively. This divergence implies that there was excess AB in the experimental aliquot or insufficient ABin the control aliquot, which would have inflated or deflated their respective results.

The second data point in Figure 5 takes place shortly after the respective addition of tau and buffer to the experimental and control aliquots. A dip is present due to temporary dissociation of the AB. At this point the tau’s presence will have marginally elevated the experimental aliquot’s baseline reading. Ideally, an inert substance with the same molar mass as tau should have replaced buffer in the AB control aliquot to control for mass.

Post-dissociation, the average aggregation rate in the experimental aliquot (Figure 6) was 1.5195 RFUs/min, approximately 1.2 times as fast as the AB control aliquot’s rate of 1.2383. Controlled experiments have shown that direct interaction of soluble tau protein with AB 1-42 induces tau aggregation and hyperphosphorylation12 and AB disassembly.13 As such, the post-dissociation aggregation rate in the experimental aliquot was likely the sum of tau aggregation and simultaneous AB disaggregation. It is notable that the tau achieved a higher aggregation rate than the control AB, even as the experimental aliquot’s disassembling AB detracted from the overall reading.

It is also possible that the tau helped to stabilize the AB after dissociation. AB fibrils are cylindrical in structure, but AB oligomers incorporate stacks of beta sheets.AB beta sheets are likely to contain residues such as Pro at the edges to minimize chances of self-aggregation.15 Tau helps to stabilize microtubules by binding to residues between heterodimers, proteins made up of two different polypeptide chains that have similar but unidentical subunits. Tau could also serve a similar anchor function for AB oligomers. The temporary dissociation of AB might have exposed adequate surface area for the tau to begin a disaggregation feedback loop. As the tau continued to aggregate and less undistorted tau remained, the feedback loop would have plateaued. Succeeding aggregation would then result from whatever AB remained, unless the aggregated tau and AB dissociate and repeat the cycle on a lesser scale.

One margin of error exists at the first data point (Figure 4), which represents the addition of the initial analyte. A larger error margin exists at the second data point, which is after the second analyte was introduced and temporarily dissociated the first analyte.

The experimental aliquot’s measurements were shown to be consistently higher than that of the AB control aliquot (Figures 4, 5, 6). Yet the initial range of aggregation displayed by the experimental aliquot falls largely within the error bound for the AB control. Additional trials should have taken place to more accurately confirm how the two aggregation rates compare. Scanning was also conducted at uneven and infrequent increments, which decreased the likelihood of obtaining data that accurately reflected the changes in each aliquot.

Conclusion

The outcome of the experiment does not support the hypothesis. While the aggregation rate was 5.5 times faster in the experimental tau-AB aliquot than in the AB control, the aggregation is suspected to originate mainly from tau rather than AB.

Further Research

Future studies are needed to determine the nature of in vivo interaction between AB and tau preceding plaque and tangle formation, as well as the conformational changes induced in both proteins. Hyperphosphorylation of tau occurs shortly before apoptosis, further highlighting the need to consider interactions between different versions of AB and tau. Another potential study is to introduce tau to ABin vitro after different time periods and observe what conformational changes take place. Many drug companies are focused on inhibiting the cytotoxic AB fibrillization process as a potential treatment for Alzheimer’s. Tau could play a major role in the search for an effective inhibition strategy due to its central role in Alzheimer’s, indirect influence on AB plaque formation and ability to inhibit AB aggregation at the cost of self-aggregation.13 A setup involving in vivo analysis of the neuron after it has been punctured by AB oligomers could identify other candidates that promote AB and tau aggregation. There is also the question of whether tau functions as a stabilizing molecule for AB at any point in its pathology, and how such a role contributes to the overall onset of Alzheimer’s. One might also investigate whether tau’s ability to stabilize AB can lead to cycles of AB aggregation and disassembly.

Acknowledgements

I would like to thank Dr. John Coller and Dr. Vanita of the Stanford Functional Genomics Facility and Dr. Kashif Ahmad of Northwestern Health Sciences University for their invaluable help in planning and conducting the experiment. My gratitude also goes to Ms. Jennifer Norman and Ms. Barbara Monks of Enzo Life Sciences for their generous support and guidance. I am also grateful to Johns Hopkins University for giving me the opportunity to conduct this experiment as part of its Cogito Research Awards program. Finally, I would like to thank my family for their wholehearted encouragement throughout the duration of this project.

Bio StatementBrent is a rising senior at Gunn High School in Palo Alto, California. He enjoys running, writing, and playing the clarinet. His scientific interests are centered around neuroscience and extraterrestrial life.